a case study and solution to implement market strategy with implementation of analytics.

1. Movie Magic: a case study for strategy
implementation with analytics
Customer Segmentation, Personalization & Strategies
Conceptualized & Created by: Ashish Kumar Singh

2. The case
 We would like you to prepare a short presentation on MovieMagic as outlined below.
 MovieMagic offer two types of service, both of which are to be considered in this presentation:
 MovieMagic by post – receive DVDs of your choice through the post
 MovieMagic instant – stream films through the internet
 MovieMagic have several databases:
 1. Names and addresses for all their customers and when they joined
 2. All films, DVDs and games rented (or streamed) by each customer and when
 3. Subscription package held by each customer, and how this has changed over time
 How should they use this data to treat their customers differently?
 In order to grow further and compete they have identified that they need to take a more
structured and strategic approach; putting customer data at the core of their decisions.
 How would you use this data to get an understanding of MovieMagic customers?
 How would this understanding help MovieMagic in marketing to the customers?
 What else, besides marketing could this information help MovieMagic with?
 How could they use this data to personalise the service – for example, with the films that they
recommend to their customers?

3. OBJECTIVE,SCOPE & ASSUMPTIONS
Objective Scope Assumptions
For the • Pan India • Volume vs.
MovieMagic Geography Value based
Customer Base: coverage analysis
• Country • Customer data
• Create a
level mandatorily has
Customer analysis address
Segmentation • Micro level [location].
Framework limits to city* • Micro level
• Personalizatio • Data defined as the
n sufficiency lowest level
• Derive limited to where
Strategies mentioned heterogeneous
*Segmentation is possible where heterogeneity resources. patterns are
is observed. Level at which homogenous clusters will be obtained
will be disregarded and +1 level will be defined as base micro level. visible.

4. APPROACH
 Context  Approach and Strategy
MovieMagic offerings Data Architecture Model Development Deriving Strategies
need to be analyzed
with respect to usage − Databases are created − Classification is done – Defining customers via
patterns, customer using various sources: based on Volume vs. metrics in terms of
base and behavior, − Customer
Value concept. clusters created for
sales & product each branch.
− Technique used:
− Media – Personalization
portfolio and come up − Cluster analysis
− Usage,etc. exercise for each
with strategies − RFM Technique cluster.
backed by customer − Common linkages are
created using Primary − Clusters/Groups – Strategy derived for
understanding & keys,IDs created based on each segment:
personalization. independent metrics – Financial
− New data definitions are available for each of the
derived.eg.current – Marketing
categories.
inventory,turn-around- – Sales
− Prediction models
time,etc.
developed for each – Supply Chain.
branch of fishbone.

5. DATA ARCHITECTURE
Subscription Description
Custom Name Addres Email Joined *Custo Subscri Subscri
ID
er ID s Date mer ption ID ption
Type Date 1 Online Yearly
Subscription
Customer Database 2 Offline Yearly
DB
Custom Media Date of Period Quantity Price
er ID ID Rent 3 Online Monthly
4 Offline Monthly
Rent Logbook DB
Cat. ID Descr. Class
Media Media Type Categor Invento Date Rented 1 Genre Movie
ID Name y ID ry (Q) Time Quantit
2 Starcast Movie
Media Category
Stamp y
3 Released Movie
[Movie/ Movie/
DB
Game Game 4 Languag Movie
Name] Media Database e
5 PC Game
6 PS Game
*Customer Type:Subscriber Online,Subscriber Offline,Repeater Online,Repeater Offline,One 7 Genre Game
Time Online,One Time

6. METHODOLOGIES:CLUSTERING/PREDICT
Segmentation
Offline Online
Rent Subscription Subscription Non-Subscribers
OneTime Repeaters Yearly/Monthly Yearly/Monthly OneTime Repeaters
Cluster Function Cluster Cluster Function of: Cluster Function of: Cluster Cluster
of: Function of: -DatetimeStamp -DatetimeStamp Function of: Function of:
-DatetimeStamp
- -Geography -Geography - -
-Geography
-Media Category
DatetimeStam -Media Category -Media Category DatetimeStamp Datetimestamp
-Media Type p -MediaType -MediaType -Geography -Geography
-No. of times -Subscription type -Subscription type - -
rented. -No. of times -No. of times MediaCategory MediaCategory
-Geography subscribed subscribed MediaType -MediaType
- -No. of times -No. of times -Browsing -No. of times
MediaCategory discontinued Discontinued history bought
-MediaType -Browsing history -Browsing
history
For each of the Fishbone branch>>Subset of data obtained>Clustering/RFM Technique Used>Model

7. IMPLEMENTATION
Sales Strategy Financial Strategy Marketing Strategy Supply Chain Strategy
 USAGE PATTERN:  DISCOUNTING:  GEO SPECIFIC  STOCKOUT/BACKLOG:
Discounting to ADVERTISING: More predict inventory to avoid
Within X days of
clusters of users stockouts,calculate
release, Y% of extra advertising in less
based on profit Adjusted Turn Around
streaming over base generation, less penetrating areas wrt Time based on
and thereafter Z% of penetration, usage index, Consumption Pattern for
extra rent over base opportunity index.Like competitive scenarios. each branch of Fishbone.
value after X days. Hike Prices when  TARGET  RED FLAGS:Flagging
demand more in
 COMBO PACKS: MARKETING based Users which are probable
streamline for a
Creating **combos of on usage pattern & unsubscriber/
period,pattern of
DVDs to push sales of specific demands, discontinuation of usage
usage.
Customer Lifetime based on patterns of
Slow Mover
 SUPPLIER subscription packages
DVDs,Contra Value.
NEGOTIATION: they used.
Sales[Demanding Based on usage
clubbed with non-  DISTRIBUTION
pattern, demand NETWORK: local network
demanding] forecasting, days of at more demanding
payable outstanding areas.
can be negotiated with
Personalization: Creating suppliers of users
the portfolio at Individual level and implementing above
strategies.
**DVD Types:1 movie/game pack, N in 1 pack,Combo Packs,Star Packs,Vintage packs,etc.